liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Strokes detection for skeletonisation of characters shapes
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology. (KPLAB)ORCID iD: 0000-0003-3011-1505
2014 (English)In: Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, Part II / [ed] George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Chandra Kambhamettu, Maha El Choubassi, Zhigang Deng, Mark Carlson, Springer, 2014, 510-520 p.Conference paper, Published paper (Refereed)
Abstract [en]

Skeletonisation is a key process in character recognition in natural images. Under the assumption that a character is made of a stroke of uniform colour, with small variation in thickness, the process of recognising characters can be decomposed in the three steps. First the image is segmented, then each segment is transformed into a set of connected strokes (skeletonisation), which are then abstracted in a descriptor that can be used to recognise the character. The main issue with skeletonisation is the sensitivity with noise, and especially, the presence of holes in the masks. In this article, a new method for the extraction of strokes is presented, which address the problem of holes in the mask and does not use any parameters.

Place, publisher, year, edition, pages
Springer, 2014. 510-520 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 8888
Keyword [en]
Texts recognition
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-112542DOI: 10.1007/978-3-319-14364-4_49ISI: 000354700300049ISBN: 978-3-319-14364-4 (print)ISBN: 978-3-319-14363-7 (print)OAI: oai:DiVA.org:liu-112542DiVA: diva2:767316
Conference
ISVC 2014
Projects
CADICS; ELLIIT; CUAS
Funder
Swedish Research CouncilLinnaeus research environment CADICSELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Foundation for Strategic Research
Available from: 2014-12-01 Created: 2014-12-01 Last updated: 2017-02-13Bibliographically approved

Open Access in DiVA

fulltext(558 kB)162 downloads
File information
File name FULLTEXT01.pdfFile size 558 kBChecksum SHA-512
3de6bde36f73dec03ddbbdab6487aec1420fd022ffe96e450dd08bc5a7529965f71378a639e65287b04862bdf8b7bfac2915dae54e50733b5be1d33111bc31e1
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Berger, Cyrille

Search in DiVA

By author/editor
Berger, Cyrille
By organisation
Artificial Intelligence and Integrated Computer SystemsThe Institute of Technology
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 162 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 179 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf